----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  D:\Vicard\VV\re\inprogress\BRV\results\Figure3.log
  log type:  text
 opened on:  29 Sep 2017, 18:11:53

. 
. 
. 
. *****************
. * Table A.25   *
. ***********************************************************************
. *
. foreach var in "fe_qty" "fe_uv_nojkt" {
  2.         foreach ele in "ele1" {
  3.         use $Output\dataset_brv_fe, clear
  4.         sort ijk year
  5.         g dres_`var' = d.res_`var'
  6.         collapse (mean) quantity_l1 (sd) var_`var' = dres_`var' (count) nb_`var' = dres_`var', by(country prod entry_`ele' year)
  7.         *
.         gen age_`ele' = year - entry_`ele' 
  8.         g size_l1     = log(quantity_l1)
  9.         *
.         tab age_`ele', gen(aged)
 10.         replace aged10 = 1 if age_`ele'>9
 11.         drop aged11
 12.         tab year, gen(yeard)
 13.         *
.         egen cohort = group(entry_`ele' country prod)
 14.         tsset cohort year
 15.         global condition  "entry_ele!=1994 & entry_ele!=1995"
 16.         *
.         label var nb_`res'      "\# observations"
 17.         label var size_l1               "Sales$ _{t-1}$"
 18.         label var age_`ele'     "Experience, `var'"
 19.         label var nb_`res'      "\# observations"
 20.         label var age_`ele'             "Age$_{ijkt}$" 
 21.         label var aged1                 "Age$_{ijkt}=2$" 
 22.         label var aged2                 "Age$_{ijkt}=3$" 
 23.         label var aged3                 "Age$_{ijkt}=4$" 
 24.         label var aged4                 "Age$_{ijkt}=5$" 
 25.         label var aged5                 "Age$_{ijkt}=6$" 
 26.         label var aged6                 "Age$_{ijkt}=7$" 
 27.         label var aged8                 "Age$_{ijkt}=8$"
 28.         label var aged9                 "Age$_{ijkt}=9$"
 29.         label var aged10                "Age$_{ijkt}=10$"
 30.         *
.         eststo: areg var_`var' age_`ele'                                if $condition, a(cohort) cluster(cohort)
 31.         eststo: areg var_`var' aged3-aged10                     if $condition, a(cohort) cluster(cohort)
 32.                 * predict *
.                 preserve
 33.                 predict pred_var_`var' if e(sample), xb
 34.                 keep country prod year pred_var_`var' age_ele1
 35.                 replace age_ele1 = age_ele1+1
 36.                 replace age_ele1 = 10 if age_ele1>9     
 37.                 save $results\pred_variance_`var', replace
 38.                 restore 
 39.         eststo: areg var_`var' age_`ele' nb_`res'                       if $condition, a(cohort) cluster(cohort)
 40.         
.         /* ESTIMATIONS CONDITIONAL ON SURVIVAL 6 YEARS */
.         di "ESTIMATIONS CONDITIONAL ON SURVIVAL  - `var'"
 41.         use $Output\dataset_brv_fe, clear
 42.         sort ijk year
 43.         g dres_`var' = d.res_`var'
 44.         keep if age_`ele'_max>=9 & age_`ele'<=9
 45.         collapse (mean) quantity_l1 (sd) var_`var' = dres_`var' (count) nb_`var' = dres_`var', by(country prod entry_`ele' year)
 46.         *
.         gen age_`ele' = year - entry_`ele' 
 47.         g size_l1    = log(quantity_l1)
 48.         *
.         tab age_`ele', gen(aged)
 49.         tab year, gen(yeard)
 50.         *
.         egen cohort = group(entry_`ele' country prod)
 51.         tsset cohort year
 52.         *
.         label var nb_`res'      "\# observations"
 53.         label var size_l1               "Size$ _{t-1}$"
 54.         label var age_`ele'             "Age$_{ijkt}$" 
 55.         label var aged1                 "Age$_{ijkt}=2$" 
 56.         label var aged2                 "Age$_{ijkt}=3$" 
 57.         label var aged3                 "Age$_{ijkt}=4$" 
 58.         label var aged4                 "Age$_{ijkt}=5$" 
 59.         label var aged5                 "Age$_{ijkt}=6$" 
 60.         label var aged6                 "Age$_{ijkt}=7$" 
 61.         label var aged8                 "Age$_{ijkt}=8$"
 62.         label var aged9                 "Age$_{ijkt}=9$"
 63.         *
.         eststo: areg var_`var' age_`ele' nb_`res' if $condition, a(cohort) cluster(cohort)
 64.                 
.         }
 65.         }
(3,328,694 missing values generated)
(714,740 missing values generated)

   age_ele1 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |    711,307       28.10       28.10
          1 |    455,852       18.01       46.11
          2 |    354,509       14.00       60.11
          3 |    261,626       10.33       70.44
          4 |    197,164        7.79       78.23
          5 |    151,662        5.99       84.22
          6 |    118,034        4.66       88.89
          7 |     90,414        3.57       92.46
          8 |     69,981        2.76       95.22
          9 |     53,122        2.10       97.32
         10 |     39,756        1.57       98.89
         11 |     28,071        1.11      100.00
------------+-----------------------------------
      Total |  2,531,498      100.00
(67,827 real changes made)

       Year |      Freq.     Percent        Cum.
------------+-----------------------------------
       1996 |    161,009        6.36        6.36
       1997 |    197,675        7.81       14.17
       1998 |    221,688        8.76       22.93
       1999 |    238,461        9.42       32.35
       2000 |    258,095       10.20       42.54
       2001 |    271,559       10.73       53.27
       2002 |    282,410       11.16       64.42
       2003 |    288,571       11.40       75.82
       2004 |    301,753       11.92       87.74
       2005 |    310,277       12.26      100.00
------------+-----------------------------------
      Total |  2,531,498      100.00
       panel variable:  cohort (unbalanced)
        time variable:  year, 1996 to 2005, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   1, 181275)   =    2553.66
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6033
                                                Adj R-squared     =     0.3194
                                                Root MSE          =     0.6225

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
  var_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele1 |  -.0512535   .0010142   -50.53   0.000    -.0532414   -.0492656
       _cons |   1.144715    .002498   458.25   0.000     1.139819    1.149611
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est3 stored)

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   8, 181275)   =     381.72
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6046
                                                Adj R-squared     =     0.3216
                                                Root MSE          =     0.6215

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
  var_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.1100531   .0037081   -29.68   0.000    -.1173209   -.1027853
       aged4 |  -.1688074   .0046065   -36.65   0.000    -.1778361   -.1597787
       aged5 |  -.2111341    .005491   -38.45   0.000    -.2218963   -.2003718
       aged6 |  -.2356287   .0063504   -37.10   0.000    -.2480754   -.2231821
       aged7 |  -.2691738   .0075385   -35.71   0.000     -.283949   -.2543985
       aged8 |  -.3030735   .0092104   -32.91   0.000    -.3211257   -.2850213
       aged9 |  -.2949197   .0121183   -24.34   0.000    -.3186712   -.2711682
      aged10 |   -.337563   .0179739   -18.78   0.000    -.3727915   -.3023345
       _cons |   1.122047   .0020071   559.03   0.000     1.118113    1.125981
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est4 stored)
(2,096,905 missing values generated)
(2,531,498 real changes made)
(67,827 real changes made)
(note: file results\pred_variance_fe_qty.dta not found)
file results\pred_variance_fe_qty.dta saved

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   2, 181275)   =    1474.73
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6036
                                                Adj R-squared     =     0.3200
                                                Root MSE          =     0.6222

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
  var_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele1 |  -.0449092   .0012417   -36.17   0.000    -.0473428   -.0424755
   nb_fe_qty |   .0076936   .0006842    11.25   0.000     .0063527    .0090346
       _cons |   1.099937   .0050457   218.00   0.000     1.090048    1.109826
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est5 stored)
ESTIMATIONS CONDITIONAL ON SURVIVAL  - fe_qty
(3,328,694 missing values generated)
(5,865,894 observations deleted)
(23,791 missing values generated)

   age_ele1 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |     22,302        4.09        4.09
          1 |     34,177        6.27       10.37
          2 |     68,536       12.58       22.95
          3 |     69,658       12.79       35.74
          4 |     69,941       12.84       48.58
          5 |     70,068       12.86       61.44
          6 |     70,133       12.87       74.31
          7 |     69,941       12.84       87.15
          8 |     69,981       12.85      100.00
------------+-----------------------------------
      Total |    544,737      100.00

       Year |      Freq.     Percent        Cum.
------------+-----------------------------------
       1996 |     55,720       10.23       10.23
       1997 |     69,104       12.69       22.91
       1998 |     69,491       12.76       35.67
       1999 |     69,808       12.81       48.49
       2000 |     70,153       12.88       61.36
       2001 |     70,085       12.87       74.23
       2002 |     70,092       12.87       87.10
       2003 |     35,236        6.47       93.57
       2004 |     23,401        4.30       97.86
       2005 |     11,647        2.14      100.00
------------+-----------------------------------
      Total |    544,737      100.00
       panel variable:  cohort (unbalanced)
        time variable:  year, 1996 to 2005, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =     44,421
                                                F(   2,   5950)   =      65.34
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3020
                                                Adj R-squared     =     0.1939
                                                Root MSE          =     0.6080

                             (Std. Err. adjusted for 5,951 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
  var_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele1 |  -.0180445   .0015794   -11.42   0.000    -.0211407   -.0149482
   nb_fe_qty |   .0061586   .0060719     1.01   0.310    -.0057444    .0180617
       _cons |   .8970008   .0191571    46.82   0.000     .8594459    .9345556
-------------+----------------------------------------------------------------
      cohort |   absorbed                                    (5951 categories)
(est6 stored)
(3,328,694 missing values generated)
(714,740 missing values generated)

   age_ele1 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |    711,307       28.10       28.10
          1 |    455,852       18.01       46.11
          2 |    354,509       14.00       60.11
          3 |    261,626       10.33       70.44
          4 |    197,164        7.79       78.23
          5 |    151,662        5.99       84.22
          6 |    118,034        4.66       88.89
          7 |     90,414        3.57       92.46
          8 |     69,981        2.76       95.22
          9 |     53,122        2.10       97.32
         10 |     39,756        1.57       98.89
         11 |     28,071        1.11      100.00
------------+-----------------------------------
      Total |  2,531,498      100.00
(67,827 real changes made)

       Year |      Freq.     Percent        Cum.
------------+-----------------------------------
       1996 |    161,009        6.36        6.36
       1997 |    197,675        7.81       14.17
       1998 |    221,688        8.76       22.93
       1999 |    238,461        9.42       32.35
       2000 |    258,095       10.20       42.54
       2001 |    271,559       10.73       53.27
       2002 |    282,410       11.16       64.42
       2003 |    288,571       11.40       75.82
       2004 |    301,753       11.92       87.74
       2005 |    310,277       12.26      100.00
------------+-----------------------------------
      Total |  2,531,498      100.00
       panel variable:  cohort (unbalanced)
        time variable:  year, 1996 to 2005, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   1, 181275)   =    2053.51
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6779
                                                Adj R-squared     =     0.4474
                                                Root MSE          =     0.3598

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
var_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele1 |  -.0285275   .0006295   -45.32   0.000    -.0297614   -.0272937
       _cons |   .5683923   .0015505   366.59   0.000     .5653534    .5714313
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est7 stored)

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   8, 181275)   =     322.01
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6791
                                                Adj R-squared     =     0.4494
                                                Root MSE          =     0.3592

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
var_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.0655652   .0021578   -30.39   0.000    -.0697943    -.061336
       aged4 |  -.0981952   .0027239   -36.05   0.000     -.103534   -.0928564
       aged5 |  -.1199381   .0032459   -36.95   0.000       -.1263   -.1135762
       aged6 |  -.1343067   .0037494   -35.82   0.000    -.1416555   -.1269578
       aged7 |  -.1477437   .0044454   -33.24   0.000    -.1564567   -.1390308
       aged8 |  -.1640467   .0053704   -30.55   0.000    -.1745725   -.1535209
       aged9 |  -.1711737   .0069842   -24.51   0.000    -.1848626   -.1574847
      aged10 |   -.184502   .0106472   -17.33   0.000    -.2053704   -.1636337
       _cons |   .5576271   .0012205   456.89   0.000      .555235    .5600192
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est8 stored)
(2,096,905 missing values generated)
(2,531,498 real changes made)
(67,827 real changes made)
(note: file results\pred_variance_fe_uv_nojkt.dta not found)
file results\pred_variance_fe_uv_nojkt.dta saved

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   2, 181275)   =    1117.22
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6782
                                                Adj R-squared     =     0.4480
                                                Root MSE          =     0.3597

                             (Std. Err. adjusted for 181,276 clusters in cohort)
--------------------------------------------------------------------------------
               |               Robust
var_fe_uv_no~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
      age_ele1 |  -.0244507   .0007636   -32.02   0.000    -.0259473   -.0229542
nb_fe_uv_nojkt |   .0049438   .0004704    10.51   0.000     .0040218    .0058658
         _cons |   .5396183   .0032423   166.43   0.000     .5332634    .5459731
---------------+----------------------------------------------------------------
        cohort |   absorbed                                  (181276 categories)
(est9 stored)
ESTIMATIONS CONDITIONAL ON SURVIVAL  - fe_uv_nojkt
(3,328,694 missing values generated)
(5,865,894 observations deleted)
(23,791 missing values generated)

   age_ele1 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |     22,302        4.09        4.09
          1 |     34,177        6.27       10.37
          2 |     68,536       12.58       22.95
          3 |     69,658       12.79       35.74
          4 |     69,941       12.84       48.58
          5 |     70,068       12.86       61.44
          6 |     70,133       12.87       74.31
          7 |     69,941       12.84       87.15
          8 |     69,981       12.85      100.00
------------+-----------------------------------
      Total |    544,737      100.00

       Year |      Freq.     Percent        Cum.
------------+-----------------------------------
       1996 |     55,720       10.23       10.23
       1997 |     69,104       12.69       22.91
       1998 |     69,491       12.76       35.67
       1999 |     69,808       12.81       48.49
       2000 |     70,153       12.88       61.36
       2001 |     70,085       12.87       74.23
       2002 |     70,092       12.87       87.10
       2003 |     35,236        6.47       93.57
       2004 |     23,401        4.30       97.86
       2005 |     11,647        2.14      100.00
------------+-----------------------------------
      Total |    544,737      100.00
       panel variable:  cohort (unbalanced)
        time variable:  year, 1996 to 2005, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =     44,421
                                                F(   2,   5950)   =      29.78
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3936
                                                Adj R-squared     =     0.2998
                                                Root MSE          =     0.3311

                               (Std. Err. adjusted for 5,951 clusters in cohort)
--------------------------------------------------------------------------------
               |               Robust
var_fe_uv_no~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
      age_ele1 |  -.0071724    .000933    -7.69   0.000    -.0090015   -.0053433
nb_fe_uv_nojkt |   .0050498    .003668     1.38   0.169    -.0021407    .0122404
         _cons |    .400849   .0116777    34.33   0.000     .3779565    .4237415
---------------+----------------------------------------------------------------
        cohort |   absorbed                                    (5951 categories)
(est10 stored)

. set linesize 250

. esttab, mtitles drop(_cons) b(%5.3f) se(%5.3f) compress r2 starlevels(c 0.1 b 0.05 a 0.01)  se 

------------------------------------------------------------------------------------------------------------------------
                 (1)        (2)        (3)        (4)        (5)        (6)        (7)        (8)        (9)       (10) 
                est1       est2       est3       est4       est5       est6       est7       est8       est9      est10 
------------------------------------------------------------------------------------------------------------------------
aged2          0.317a    -0.038a                                                                                        
             (0.015)    (0.014)                                                                                         

aged3          0.447a    -0.047a               -0.110a                                     -0.066a                      
             (0.018)    (0.014)               (0.004)                                     (0.002)                       

aged4          0.511a    -0.042a               -0.169a                                     -0.098a                      
             (0.019)    (0.014)               (0.005)                                     (0.003)                       

aged5          0.563a    -0.047a               -0.211a                                     -0.120a                      
             (0.021)    (0.015)               (0.005)                                     (0.003)                       

aged6          0.594a    -0.054a               -0.236a                                     -0.134a                      
             (0.023)    (0.015)               (0.006)                                     (0.004)                       

aged7          0.595a    -0.050a               -0.269a                                     -0.148a                      
             (0.022)    (0.015)               (0.008)                                     (0.004)                       

aged8          0.571a    -0.049a               -0.303a                                     -0.164a                      
             (0.022)    (0.015)               (0.009)                                     (0.005)                       

aged9          0.563a    -0.043a               -0.295a                                     -0.171a                      
             (0.022)    (0.015)               (0.012)                                     (0.007)                       

aged10         0.496a    -0.047a               -0.338a                                     -0.185a                      
             (0.021)    (0.015)               (0.018)                                     (0.011)                       

age_ele1                            -0.051a               -0.045a    -0.018a    -0.029a               -0.024a    -0.007a
                                   (0.001)               (0.001)    (0.002)    (0.001)               (0.001)    (0.001) 

nb_fe_qty                                                  0.008a     0.006                                             
                                                         (0.001)    (0.006)                                             

nb_fe_uv~t                                                                                             0.005a     0.005 
                                                                                                     (0.000)    (0.004) 
------------------------------------------------------------------------------------------------------------------------
N             121775     121775     434593     434593     434593      44421     434593     434593     434593      44421 
R-sq           0.018      0.001      0.603      0.605      0.604      0.302      0.678      0.679      0.678      0.394 
------------------------------------------------------------------------------------------------------------------------
Standard errors in parentheses
c p<0.1, b p<0.05, a p<0.01

. esttab, mtitles drop(_cons) b(%5.3f) se(%5.3f) r2  starlevels({$^c$} 0.1 {$^b$} 0.05 {$^a$} 0.01) se tex label  title() 

{
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\begin{tabular}{l*{10}{c}}
\hline\hline
                    &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}&\multicolumn{1}{c}{(4)}&\multicolumn{1}{c}{(5)}&\multicolumn{1}{c}{(6)}&\multicolumn{1}{c}{(7)}&\multicolumn{1}{c}{(8)}&\multicolumn{1}{c}{(9)}&\multicolumn{
> 1}{c}{(10)}\\
                    &\multicolumn{1}{c}{est1}&\multicolumn{1}{c}{est2}&\multicolumn{1}{c}{est3}&\multicolumn{1}{c}{est4}&\multicolumn{1}{c}{est5}&\multicolumn{1}{c}{est6}&\multicolumn{1}{c}{est7}&\multicolumn{1}{c}{est8}&\multicolumn{1}{c}{est9}&\mul
> ticolumn{1}{c}{est10}\\
\hline
Age{ijkt}=3$        &       0.317{$^a$}&      -0.038{$^a$}&                  &                  &                  &                  &                  &                  &                  &                  \\
                    &     (0.015)      &     (0.014)      &                  &                  &                  &                  &                  &                  &                  &                  \\
[1em]
Age{ijkt}=4$        &       0.447{$^a$}&      -0.047{$^a$}&                  &      -0.110{$^a$}&                  &                  &                  &      -0.066{$^a$}&                  &                  \\
                    &     (0.018)      &     (0.014)      &                  &     (0.004)      &                  &                  &                  &     (0.002)      &                  &                  \\
[1em]
Age{ijkt}=5$        &       0.511{$^a$}&      -0.042{$^a$}&                  &      -0.169{$^a$}&                  &                  &                  &      -0.098{$^a$}&                  &                  \\
                    &     (0.019)      &     (0.014)      &                  &     (0.005)      &                  &                  &                  &     (0.003)      &                  &                  \\
[1em]
Age{ijkt}=6$        &       0.563{$^a$}&      -0.047{$^a$}&                  &      -0.211{$^a$}&                  &                  &                  &      -0.120{$^a$}&                  &                  \\
                    &     (0.021)      &     (0.015)      &                  &     (0.005)      &                  &                  &                  &     (0.003)      &                  &                  \\
[1em]
Age{ijkt}=7$        &       0.594{$^a$}&      -0.054{$^a$}&                  &      -0.236{$^a$}&                  &                  &                  &      -0.134{$^a$}&                  &                  \\
                    &     (0.023)      &     (0.015)      &                  &     (0.006)      &                  &                  &                  &     (0.004)      &                  &                  \\
[1em]
age\_ele1==     6.0000&       0.595{$^a$}&      -0.050{$^a$}&                  &      -0.269{$^a$}&                  &                  &                  &      -0.148{$^a$}&                  &                  \\
                    &     (0.022)      &     (0.015)      &                  &     (0.008)      &                  &                  &                  &     (0.004)      &                  &                  \\
[1em]
Age{ijkt}=8$        &       0.571{$^a$}&      -0.049{$^a$}&                  &      -0.303{$^a$}&                  &                  &                  &      -0.164{$^a$}&                  &                  \\
                    &     (0.022)      &     (0.015)      &                  &     (0.009)      &                  &                  &                  &     (0.005)      &                  &                  \\
[1em]
Age{ijkt}=9$        &       0.563{$^a$}&      -0.043{$^a$}&                  &      -0.295{$^a$}&                  &                  &                  &      -0.171{$^a$}&                  &                  \\
                    &     (0.022)      &     (0.015)      &                  &     (0.012)      &                  &                  &                  &     (0.007)      &                  &                  \\
[1em]
aged10              &       0.496{$^a$}&      -0.047{$^a$}&                  &      -0.338{$^a$}&                  &                  &                  &      -0.185{$^a$}&                  &                  \\
                    &     (0.021)      &     (0.015)      &                  &     (0.018)      &                  &                  &                  &     (0.011)      &                  &                  \\
[1em]
Age{ijkt}$          &                  &                  &      -0.051{$^a$}&                  &      -0.045{$^a$}&      -0.018{$^a$}&      -0.029{$^a$}&                  &      -0.024{$^a$}&      -0.007{$^a$}\\
                    &                  &                  &     (0.001)      &                  &     (0.001)      &     (0.002)      &     (0.001)      &                  &     (0.001)      &     (0.001)      \\
[1em]
nb\_fe\_qty           &                  &                  &                  &                  &       0.008{$^a$}&       0.006      &                  &                  &                  &                  \\
                    &                  &                  &                  &                  &     (0.001)      &     (0.006)      &                  &                  &                  &                  \\
[1em]
\# observations     &                  &                  &                  &                  &                  &                  &                  &                  &       0.005{$^a$}&       0.005      \\
                    &                  &                  &                  &                  &                  &                  &                  &                  &     (0.000)      &     (0.004)      \\
\hline
Observations        &      121775      &      121775      &      434593      &      434593      &      434593      &       44421      &      434593      &      434593      &      434593      &       44421      \\
\(R^{2}\)           &       0.018      &       0.001      &       0.603      &       0.605      &       0.604      &       0.302      &       0.678      &       0.679      &       0.678      &       0.394      \\
\hline\hline
\multicolumn{11}{l}{\footnotesize Standard errors in parentheses}\\
\multicolumn{11}{l}{\footnotesize {$^c$} p<0.1, {$^b$} p<0.05, {$^a$} p<0.01}\\
\end{tabular}
}

. eststo clear    

.                 
. 
. 
. *****************************************************************
. * Table A.26 Robustness: export sales, jkt in prices, control for size *
. *****************************************************************
. 
. /* export sales and jkt in prices */
. foreach var in "fe" {
  2.         foreach ele in "ele1" {
  3.         use $Output\dataset_brv_fe, clear
  4.         sort ijk year
  5.         g dres_`var' = d.res_`var'
  6.         collapse (mean) quantity_l1 (sd) var_`var' = dres_`var' (count) nb_`var' = dres_`var', by(country prod entry_`ele' year)
  7.         *
.         gen age_`ele' = year - entry_`ele' 
  8.         g size_l1     = log(quantity_l1)
  9.         *
.         
.         tab age_`ele', gen(aged)
 10.         replace aged10 = 1 if age_`ele'>9
 11.         drop aged11
 12.         tab year, gen(yeard)
 13.         *
.         egen cohort = group(entry_`ele' country prod)
 14.         tsset cohort year
 15.         global condition  "entry_ele!=1994 & entry_ele!=1995"
 16.         *
.         label var nb_`res'      "\# observations"
 17.         label var size_l1               "Sales$ _{t-1}$"
 18.         label var age_`ele'     "Experience, `var'"
 19.         label var nb_`res'      "\# observations"
 20.         label var age_`ele'             "Age$_{ijkt}$" 
 21.         label var aged1                 "Age$_{ijkt}=2$" 
 22.         label var aged2                 "Age$_{ijkt}=3$" 
 23.         label var aged3                 "Age$_{ijkt}=4$" 
 24.         label var aged4                 "Age$_{ijkt}=5$" 
 25.         label var aged5                 "Age$_{ijkt}=6$" 
 26.         label var aged6                 "Age$_{ijkt}=7+$" 
 27.         *
.         eststo: areg var_`var' age_`ele'                                if $condition, a(cohort) cluster(cohort)
 28.         eststo: areg var_`var' aged3-aged10                     if $condition, a(cohort) cluster(cohort)
 29.                 * predict *
.                 preserve
 30.                 predict pred_var_v if e(sample), xb
 31.                 keep country prod year pred_var_v age_ele1
 32.                 replace age_ele1 = age_ele1+1
 33.                 replace age_ele1 = 10 if age_ele1>9
 34.                 save $results\pred_variance_v, replace
 35.                 restore 
 36.         
.         }
 37.         }
(3,328,694 missing values generated)
(714,740 missing values generated)

   age_ele1 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |    711,307       28.10       28.10
          1 |    455,852       18.01       46.11
          2 |    354,509       14.00       60.11
          3 |    261,626       10.33       70.44
          4 |    197,164        7.79       78.23
          5 |    151,662        5.99       84.22
          6 |    118,034        4.66       88.89
          7 |     90,414        3.57       92.46
          8 |     69,981        2.76       95.22
          9 |     53,122        2.10       97.32
         10 |     39,756        1.57       98.89
         11 |     28,071        1.11      100.00
------------+-----------------------------------
      Total |  2,531,498      100.00
(67,827 real changes made)

       Year |      Freq.     Percent        Cum.
------------+-----------------------------------
       1996 |    161,009        6.36        6.36
       1997 |    197,675        7.81       14.17
       1998 |    221,688        8.76       22.93
       1999 |    238,461        9.42       32.35
       2000 |    258,095       10.20       42.54
       2001 |    271,559       10.73       53.27
       2002 |    282,410       11.16       64.42
       2003 |    288,571       11.40       75.82
       2004 |    301,753       11.92       87.74
       2005 |    310,277       12.26      100.00
------------+-----------------------------------
      Total |  2,531,498      100.00
       panel variable:  cohort (unbalanced)
        time variable:  year, 1996 to 2005, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   1, 181275)   =    2539.44
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5739
                                                Adj R-squared     =     0.2690
                                                Root MSE          =     0.5361

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
      var_fe |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele1 |  -.0435658   .0008645   -50.39   0.000    -.0452602   -.0418713
       _cons |   .9979321   .0021293   468.67   0.000     .9937587    1.002105
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est1 stored)

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   8, 181275)   =     376.06
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5752
                                                Adj R-squared     =     0.2712
                                                Root MSE          =     0.5353

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
      var_fe |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.0932863    .003177   -29.36   0.000    -.0995131   -.0870594
       aged4 |  -.1394123   .0039595   -35.21   0.000    -.1471728   -.1316519
       aged5 |  -.1789409   .0047162   -37.94   0.000    -.1881846   -.1696973
       aged6 |  -.2007473   .0054588   -36.77   0.000    -.2114465   -.1900481
       aged7 |  -.2300992   .0065194   -35.29   0.000    -.2428772   -.2173213
       aged8 |  -.2519223   .0079759   -31.59   0.000    -.2675549   -.2362896
       aged9 |  -.2583819   .0103675   -24.92   0.000    -.2787021   -.2380618
      aged10 |  -.2866842   .0148006   -19.37   0.000    -.3156931   -.2576753
       _cons |   .9780361   .0017112   571.57   0.000     .9746823    .9813899
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est2 stored)
(2,096,905 missing values generated)
(2,531,498 real changes made)
(67,827 real changes made)
(note: file results\pred_variance_v.dta not found)
file results\pred_variance_v.dta saved

. 
. /* control for size */
. foreach var in "fe_qty" "fe_uv" {
  2.         foreach ele in "ele1" {
  3.         use $Output\dataset_brv_fe, clear
  4.         sort ijk year
  5.         g dres_`var' = d.res_`var'
  6.         collapse (mean) quantity_l1 (sd) var_`var' = dres_`var' (count) nb_`var' = dres_`var', by(country prod entry_`ele' year)
  7.         *
.         gen age_`ele' = year - entry_`ele' 
  8.         g size_l1     = log(quantity_l1)
  9.         *
.         tab age_`ele', gen(aged)
 10.         replace aged10 = 1 if age_`ele'>9
 11.         drop aged11
 12.         tab year, gen(yeard)
 13.         *
.         egen cohort = group(entry_`ele' country prod)
 14.         tsset cohort year
 15.         global condition  "entry_ele!=1994 & entry_ele!=1995"
 16.         *
.         label var nb_`res'      "\# observations"
 17.         label var size_l1               "Sales$ _{t-1}$"
 18.         label var age_`ele'     "Experience, `var'"
 19.         label var nb_`res'      "\# observations"
 20.         label var age_`ele'             "Age$_{ijkt}$" 
 21.         label var aged1                 "Age$_{ijkt}=2$" 
 22.         label var aged2                 "Age$_{ijkt}=3$" 
 23.         label var aged3                 "Age$_{ijkt}=4$" 
 24.         label var aged4                 "Age$_{ijkt}=5$" 
 25.         label var aged5                 "Age$_{ijkt}=6$" 
 26.         label var aged6                 "Age$_{ijkt}=7$" 
 27.         label var aged8                 "Age$_{ijkt}=8$"
 28.         label var aged9                 "Age$_{ijkt}=9$"
 29.         label var aged10                "Age$_{ijkt}=10$"
 30.         *
.         eststo: areg var_`var' age_`ele'    size_l1                     if $condition, a(cohort) cluster(cohort)
 31.         eststo: areg var_`var' aged3-aged10  size_l1                    if $condition, a(cohort) cluster(cohort)
 32.         
.         }
 33.         }
(3,328,694 missing values generated)
(714,740 missing values generated)

   age_ele1 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |    711,307       28.10       28.10
          1 |    455,852       18.01       46.11
          2 |    354,509       14.00       60.11
          3 |    261,626       10.33       70.44
          4 |    197,164        7.79       78.23
          5 |    151,662        5.99       84.22
          6 |    118,034        4.66       88.89
          7 |     90,414        3.57       92.46
          8 |     69,981        2.76       95.22
          9 |     53,122        2.10       97.32
         10 |     39,756        1.57       98.89
         11 |     28,071        1.11      100.00
------------+-----------------------------------
      Total |  2,531,498      100.00
(67,827 real changes made)

       Year |      Freq.     Percent        Cum.
------------+-----------------------------------
       1996 |    161,009        6.36        6.36
       1997 |    197,675        7.81       14.17
       1998 |    221,688        8.76       22.93
       1999 |    238,461        9.42       32.35
       2000 |    258,095       10.20       42.54
       2001 |    271,559       10.73       53.27
       2002 |    282,410       11.16       64.42
       2003 |    288,571       11.40       75.82
       2004 |    301,753       11.92       87.74
       2005 |    310,277       12.26      100.00
------------+-----------------------------------
      Total |  2,531,498      100.00
       panel variable:  cohort (unbalanced)
        time variable:  year, 1996 to 2005, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   2, 181275)   =    1297.95
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6035
                                                Adj R-squared     =     0.3198
                                                Root MSE          =     0.6223

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
  var_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele1 |   -.049414   .0010575   -46.73   0.000    -.0514866   -.0473414
     size_l1 |  -.0147616   .0023693    -6.23   0.000    -.0194055   -.0101178
       _cons |   1.252724   .0175042    71.57   0.000     1.218416    1.287032
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est3 stored)

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   9, 181275)   =     340.31
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6047
                                                Adj R-squared     =     0.3217
                                                Root MSE          =     0.6214

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
  var_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.1065915    .003863   -27.59   0.000    -.1141628   -.0990202
       aged4 |  -.1645137   .0047914   -34.34   0.000    -.1739046   -.1551227
       aged5 |  -.2063977   .0056986   -36.22   0.000    -.2175669   -.1952286
       aged6 |  -.2306377    .006539   -35.27   0.000     -.243454   -.2178213
       aged7 |  -.2640446   .0077343   -34.14   0.000    -.2792037   -.2488855
       aged8 |  -.2978969   .0093529   -31.85   0.000    -.3162283   -.2795655
       aged9 |    -.28982   .0122305   -23.70   0.000    -.3137915   -.2658485
      aged10 |  -.3319701   .0180297   -18.41   0.000    -.3673079   -.2966322
     size_l1 |  -.0075481   .0024207    -3.12   0.002    -.0122926   -.0028035
       _cons |   1.177093    .017781    66.20   0.000     1.142242    1.211943
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est4 stored)
(3,328,694 missing values generated)
(714,740 missing values generated)

   age_ele1 |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |    711,307       28.10       28.10
          1 |    455,852       18.01       46.11
          2 |    354,509       14.00       60.11
          3 |    261,626       10.33       70.44
          4 |    197,164        7.79       78.23
          5 |    151,662        5.99       84.22
          6 |    118,034        4.66       88.89
          7 |     90,414        3.57       92.46
          8 |     69,981        2.76       95.22
          9 |     53,122        2.10       97.32
         10 |     39,756        1.57       98.89
         11 |     28,071        1.11      100.00
------------+-----------------------------------
      Total |  2,531,498      100.00
(67,827 real changes made)

       Year |      Freq.     Percent        Cum.
------------+-----------------------------------
       1996 |    161,009        6.36        6.36
       1997 |    197,675        7.81       14.17
       1998 |    221,688        8.76       22.93
       1999 |    238,461        9.42       32.35
       2000 |    258,095       10.20       42.54
       2001 |    271,559       10.73       53.27
       2002 |    282,410       11.16       64.42
       2003 |    288,571       11.40       75.82
       2004 |    301,753       11.92       87.74
       2005 |    310,277       12.26      100.00
------------+-----------------------------------
      Total |  2,531,498      100.00
       panel variable:  cohort (unbalanced)
        time variable:  year, 1996 to 2005, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   2, 181275)   =    1060.94
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6764
                                                Adj R-squared     =     0.4449
                                                Root MSE          =     0.3532

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
   var_fe_uv |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele1 |  -.0260092   .0006468   -40.21   0.000    -.0272769   -.0247414
     size_l1 |  -.0127731   .0013597    -9.39   0.000    -.0154381   -.0101082
       _cons |   .6535459   .0100049    65.32   0.000     .6339365    .6731554
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est5 stored)

Linear regression, absorbing indicators         Number of obs     =    434,593
                                                F(   9, 181275)   =     286.25
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6774
                                                Adj R-squared     =     0.4465
                                                Root MSE          =     0.3526

                           (Std. Err. adjusted for 181,276 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
   var_fe_uv |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.0599816   .0022198   -27.02   0.000    -.0643323   -.0556309
       aged4 |  -.0893716   .0028011   -31.91   0.000    -.0948618   -.0838814
       aged5 |  -.1108063   .0033299   -33.28   0.000    -.1173329   -.1042797
       aged6 |  -.1240908   .0038145   -32.53   0.000    -.1315672   -.1166145
       aged7 |  -.1382259   .0045081   -30.66   0.000    -.1470616   -.1293902
       aged8 |  -.1530686   .0053879   -28.41   0.000    -.1636287   -.1425085
       aged9 |  -.1598759   .0069051   -23.15   0.000    -.1734098    -.146342
      aged10 |   -.170025    .010757   -15.81   0.000    -.1911086   -.1489415
     size_l1 |  -.0086032   .0013956    -6.16   0.000    -.0113386   -.0058678
       _cons |   .6124618   .0102092    59.99   0.000      .592452    .6324717
-------------+----------------------------------------------------------------
      cohort |   absorbed                                  (181276 categories)
(est6 stored)

. 
. 
. * Robustness: other types of experience *
. 
. foreach ele in "ele2" "ele3" {
  2.         foreach var in "fe_qty" "fe_uv_nojkt" {
  3.         use $Output\dataset_brv_fe, clear
  4.         keep if entry_ele!=1994 & entry_ele!=1995
  5.         sort ijk year
  6.         g dres_`var' = d.res_`var'
  7.         collapse (mean) quantity_l1 (sd) var_`var' = dres_`var' (count) nb_`var' = res_`var', by(country prod age_`ele')
  8.         *
.         g size_l1     = log(quantity_l1)
  9.         *
.         tab age_`ele', gen(aged)
 10.         replace aged10 = 1 if age_`ele'>9
 11.         *
.         egen cohort = group(country prod)
 12.         tsset cohort age_`ele'
 13.         *
.         label var nb_`res'      "\# observations"
 14.         label var size_l1               "Size$ _{t-1}$"
 15.         label var age_`ele'     "Experience, `var'"
 16.         label var nb_`res'      "\# observations"
 17.         label var age_`ele'             "Age$_{ijkt}$" 
 18.         label var aged1                 "Age$_{ijkt}=2$" 
 19.         label var aged2                 "Age$_{ijkt}=3$" 
 20.         label var aged3                 "Age$_{ijkt}=4$" 
 21.         label var aged4                 "Age$_{ijkt}=5$" 
 22.         label var aged5                 "Age$_{ijkt}=6$" 
 23.         label var aged6                 "Age$_{ijkt}=7$" 
 24.         label var aged8                 "Age$_{ijkt}=8$"
 25.         label var aged9                 "Age$_{ijkt}=9$"
 26.         label var aged10                "Age$_{ijkt}=10$"
 27.         *
.         eststo: areg var_`var' age_`ele'                                , a(cohort) cluster(cohort)
 28.         eststo: areg var_`var' aged3-aged10                     , a(cohort) cluster(cohort)
 29.         }
 30.         }
(2,692,388 observations deleted)
(2,499,101 missing values generated)
(163,179 missing values generated)

 Experience |
         by |
dest*prod / |
   reset if |
     exit 2 |
      years |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |    144,935       23.65       23.65
          2 |    110,371       18.01       41.65
          3 |     88,284       14.40       56.06
          4 |     72,341       11.80       67.86
          5 |     58,928        9.61       77.47
          6 |     47,285        7.71       85.19
          7 |     37,003        6.04       91.22
          8 |     26,990        4.40       95.63
          9 |     17,994        2.94       98.56
         10 |      8,810        1.44      100.00
------------+-----------------------------------
      Total |    612,941      100.00
(0 real changes made)
       panel variable:  cohort (unbalanced)
        time variable:  age_ele2, 1 to 10, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =    246,772
                                                F(   1,  72334)   =    3788.31
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5066
                                                Adj R-squared     =     0.3019
                                                Root MSE          =     0.5262

                            (Std. Err. adjusted for 72,335 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
  var_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele2 |  -.0525161   .0008532   -61.55   0.000    -.0541885   -.0508438
       _cons |   1.222976   .0034317   356.37   0.000      1.21625    1.229702
-------------+----------------------------------------------------------------
      cohort |   absorbed                                   (72335 categories)
(est7 stored)

Linear regression, absorbing indicators         Number of obs     =    246,772
                                                F(   8,  72334)   =     518.26
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5070
                                                Adj R-squared     =     0.3026
                                                Root MSE          =     0.5259

                            (Std. Err. adjusted for 72,335 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
  var_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.0820161   .0035823   -22.89   0.000    -.0890374   -.0749947
       aged4 |  -.1382327   .0042046   -32.88   0.000    -.1464737   -.1299917
       aged5 |  -.1878659   .0048435   -38.79   0.000    -.1973592   -.1783726
       aged6 |  -.2295694   .0055186   -41.60   0.000    -.2403859   -.2187529
       aged7 |  -.2786073   .0063908   -43.59   0.000    -.2911333   -.2660813
       aged8 |  -.3108475   .0079353   -39.17   0.000    -.3264007   -.2952942
       aged9 |  -.3460399   .0104052   -33.26   0.000     -.366434   -.3256458
      aged10 |  -.4330024    .017567   -24.65   0.000    -.4674336   -.3985713
       _cons |   1.135519   .0022498   504.72   0.000      1.13111    1.139929
-------------+----------------------------------------------------------------
      cohort |   absorbed                                   (72335 categories)
(est8 stored)
(2,692,388 observations deleted)
(2,499,101 missing values generated)
(163,179 missing values generated)

 Experience |
         by |
dest*prod / |
   reset if |
     exit 2 |
      years |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |    144,935       23.65       23.65
          2 |    110,371       18.01       41.65
          3 |     88,284       14.40       56.06
          4 |     72,341       11.80       67.86
          5 |     58,928        9.61       77.47
          6 |     47,285        7.71       85.19
          7 |     37,003        6.04       91.22
          8 |     26,990        4.40       95.63
          9 |     17,994        2.94       98.56
         10 |      8,810        1.44      100.00
------------+-----------------------------------
      Total |    612,941      100.00
(0 real changes made)
       panel variable:  cohort (unbalanced)
        time variable:  age_ele2, 1 to 10, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =    246,772
                                                F(   1,  72334)   =    4386.46
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5934
                                                Adj R-squared     =     0.4248
                                                Root MSE          =     0.3365

                            (Std. Err. adjusted for 72,335 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
var_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele2 |  -.0375559    .000567   -66.23   0.000    -.0386673   -.0364445
       _cons |   .6550009   .0022807   287.20   0.000     .6505308     .659471
-------------+----------------------------------------------------------------
      cohort |   absorbed                                   (72335 categories)
(est9 stored)

Linear regression, absorbing indicators         Number of obs     =    246,772
                                                F(   8,  72334)   =     601.34
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5945
                                                Adj R-squared     =     0.4263
                                                Root MSE          =     0.3361

                            (Std. Err. adjusted for 72,335 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
var_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.0687188   .0024555   -27.99   0.000    -.0735316    -.063906
       aged4 |  -.1109793   .0028599   -38.80   0.000    -.1165848   -.1053739
       aged5 |  -.1479415   .0031584   -46.84   0.000    -.1541319    -.141751
       aged6 |  -.1726784   .0035388   -48.80   0.000    -.1796144   -.1657424
       aged7 |  -.1974837   .0040567   -48.68   0.000    -.2054348   -.1895327
       aged8 |  -.2229215   .0048474   -45.99   0.000    -.2324223   -.2134207
       aged9 |  -.2514687   .0063042   -39.89   0.000    -.2638249   -.2391126
      aged10 |  -.2928585    .010002   -29.28   0.000    -.3124623   -.2732547
       _cons |   .5988753   .0015781   379.49   0.000     .5957822    .6019684
-------------+----------------------------------------------------------------
      cohort |   absorbed                                   (72335 categories)
(est10 stored)
(2,692,388 observations deleted)
(2,499,101 missing values generated)
(175,159 missing values generated)

 Experience |
         by |
 dest*prod: |
   count of |
   years of |
     export |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |    144,075       22.76       22.76
          2 |    113,380       17.91       40.67
          3 |     92,787       14.66       55.32
          4 |     76,948       12.15       67.48
          5 |     62,764        9.91       77.39
          6 |     50,078        7.91       85.30
          7 |     38,660        6.11       91.41
          8 |     27,602        4.36       95.77
          9 |     17,994        2.84       98.61
         10 |      8,810        1.39      100.00
------------+-----------------------------------
      Total |    633,098      100.00
(0 real changes made)
       panel variable:  cohort (unbalanced)
        time variable:  age_ele3, 1 to 10, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =    251,236
                                                F(   1,  71112)   =    3595.78
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4945
                                                Adj R-squared     =     0.2950
                                                Root MSE          =     0.5325

                            (Std. Err. adjusted for 71,113 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
  var_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele3 |  -.0501983   .0008371   -59.96   0.000    -.0518391   -.0485576
       _cons |   1.219897    .003411   357.63   0.000     1.213211    1.226583
-------------+----------------------------------------------------------------
      cohort |   absorbed                                   (71113 categories)
(est11 stored)

Linear regression, absorbing indicators         Number of obs     =    251,236
                                                F(   8,  71112)   =     466.89
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4946
                                                Adj R-squared     =     0.2951
                                                Root MSE          =     0.5324

                            (Std. Err. adjusted for 71,113 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
  var_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.0633918   .0036243   -17.49   0.000    -.0704954   -.0562882
       aged4 |  -.1157506   .0042023   -27.54   0.000    -.1239872    -.107514
       aged5 |  -.1650295   .0047683   -34.61   0.000    -.1743755   -.1556836
       aged6 |  -.2105921   .0053769   -39.17   0.000    -.2211308   -.2000533
       aged7 |  -.2580604   .0062648   -41.19   0.000    -.2703394   -.2457814
       aged8 |  -.2973397   .0077921   -38.16   0.000    -.3126122   -.2820673
       aged9 |  -.3358349   .0103453   -32.46   0.000    -.3561117   -.3155582
      aged10 |  -.4232785    .017455   -24.25   0.000    -.4574902   -.3890669
       _cons |   1.127753   .0023162   486.89   0.000     1.123213    1.132293
-------------+----------------------------------------------------------------
      cohort |   absorbed                                   (71113 categories)
(est12 stored)
(2,692,388 observations deleted)
(2,499,101 missing values generated)
(175,159 missing values generated)

 Experience |
         by |
 dest*prod: |
   count of |
   years of |
     export |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |    144,075       22.76       22.76
          2 |    113,380       17.91       40.67
          3 |     92,787       14.66       55.32
          4 |     76,948       12.15       67.48
          5 |     62,764        9.91       77.39
          6 |     50,078        7.91       85.30
          7 |     38,660        6.11       91.41
          8 |     27,602        4.36       95.77
          9 |     17,994        2.84       98.61
         10 |      8,810        1.39      100.00
------------+-----------------------------------
      Total |    633,098      100.00
(0 real changes made)
       panel variable:  cohort (unbalanced)
        time variable:  age_ele3, 1 to 10, but with gaps
                delta:  1 unit

Linear regression, absorbing indicators         Number of obs     =    251,236
                                                F(   1,  71112)   =    3986.15
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5777
                                                Adj R-squared     =     0.4110
                                                Root MSE          =     0.3437

                            (Std. Err. adjusted for 71,113 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
var_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele3 |  -.0353701   .0005602   -63.14   0.000    -.0364682   -.0342721
       _cons |   .6509312   .0022827   285.16   0.000     .6464571    .6554053
-------------+----------------------------------------------------------------
      cohort |   absorbed                                   (71113 categories)
(est13 stored)

Linear regression, absorbing indicators         Number of obs     =    251,236
                                                F(   8,  71112)   =     518.03
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5781
                                                Adj R-squared     =     0.4115
                                                Root MSE          =     0.3435

                            (Std. Err. adjusted for 71,113 clusters in cohort)
------------------------------------------------------------------------------
             |               Robust
var_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.0540879   .0025087   -21.56   0.000    -.0590049   -.0491708
       aged4 |   -.090466   .0028718   -31.50   0.000    -.0960947   -.0848373
       aged5 |  -.1282543   .0031352   -40.91   0.000    -.1343994   -.1221093
       aged6 |  -.1544474   .0035004   -44.12   0.000    -.1613082   -.1475865
       aged7 |  -.1819308   .0039936   -45.56   0.000    -.1897583   -.1741033
       aged8 |  -.2093809    .004815   -43.49   0.000    -.2188183   -.1999435
       aged9 |  -.2418898   .0062715   -38.57   0.000     -.254182   -.2295976
      aged10 |  -.2826702   .0099436   -28.43   0.000    -.3021596   -.2631809
       _cons |   .5916024   .0016309   362.75   0.000     .5884058    .5947989
-------------+----------------------------------------------------------------
      cohort |   absorbed                                   (71113 categories)
(est14 stored)

. set linesize 250

. esttab, mtitles drop(_cons) b(%5.3f) se(%5.3f) compress r2 starlevels(c 0.1 b 0.05 a 0.01)  se 

--------------------------------------------------------------------------------------------------------------------------------------------------------------------
                 (1)        (2)        (3)        (4)        (5)        (6)        (7)        (8)        (9)       (10)       (11)       (12)       (13)       (14) 
                est1       est2       est3       est4       est5       est6       est7       est8       est9      est10      est11      est12      est13      est14 
--------------------------------------------------------------------------------------------------------------------------------------------------------------------
age_ele1      -0.044a               -0.049a               -0.026a                                                                                                   
             (0.001)               (0.001)               (0.001)                                                                                                    

aged3                    -0.093a               -0.107a               -0.060a               -0.082a               -0.069a               -0.063a               -0.054a
                        (0.003)               (0.004)               (0.002)               (0.004)               (0.002)               (0.004)               (0.003) 

aged4                    -0.139a               -0.165a               -0.089a               -0.138a               -0.111a               -0.116a               -0.090a
                        (0.004)               (0.005)               (0.003)               (0.004)               (0.003)               (0.004)               (0.003) 

aged5                    -0.179a               -0.206a               -0.111a               -0.188a               -0.148a               -0.165a               -0.128a
                        (0.005)               (0.006)               (0.003)               (0.005)               (0.003)               (0.005)               (0.003) 

aged6                    -0.201a               -0.231a               -0.124a               -0.230a               -0.173a               -0.211a               -0.154a
                        (0.005)               (0.007)               (0.004)               (0.006)               (0.004)               (0.005)               (0.004) 

aged7                    -0.230a               -0.264a               -0.138a               -0.279a               -0.197a               -0.258a               -0.182a
                        (0.007)               (0.008)               (0.005)               (0.006)               (0.004)               (0.006)               (0.004) 

aged8                    -0.252a               -0.298a               -0.153a               -0.311a               -0.223a               -0.297a               -0.209a
                        (0.008)               (0.009)               (0.005)               (0.008)               (0.005)               (0.008)               (0.005) 

aged9                    -0.258a               -0.290a               -0.160a               -0.346a               -0.251a               -0.336a               -0.242a
                        (0.010)               (0.012)               (0.007)               (0.010)               (0.006)               (0.010)               (0.006) 

aged10                   -0.287a               -0.332a               -0.170a               -0.433a               -0.293a               -0.423a               -0.283a
                        (0.015)               (0.018)               (0.011)               (0.018)               (0.010)               (0.017)               (0.010) 

size_l1                             -0.015a    -0.008a    -0.013a    -0.009a                                                                                        
                                   (0.002)    (0.002)    (0.001)    (0.001)                                                                                         

age_ele2                                                                        -0.053a               -0.038a                                                       
                                                                               (0.001)               (0.001)                                                        

age_ele3                                                                                                                    -0.050a               -0.035a           
                                                                                                                           (0.001)               (0.001)            
--------------------------------------------------------------------------------------------------------------------------------------------------------------------
N             434593     434593     434593     434593     434593     434593     246772     246772     246772     246772     251236     251236     251236     251236 
R-sq           0.574      0.575      0.603      0.605      0.676      0.677      0.507      0.507      0.593      0.595      0.495      0.495      0.578      0.578 
--------------------------------------------------------------------------------------------------------------------------------------------------------------------
Standard errors in parentheses
c p<0.1, b p<0.05, a p<0.01

. esttab, mtitles drop(_cons) b(%5.3f) se(%5.3f) r2  starlevels({$^c$} 0.1 {$^b$} 0.05 {$^a$} 0.01) se tex label  title() 

{
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\begin{tabular}{l*{14}{c}}
\hline\hline
                    &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}&\multicolumn{1}{c}{(4)}&\multicolumn{1}{c}{(5)}&\multicolumn{1}{c}{(6)}&\multicolumn{1}{c}{(7)}&\multicolumn{1}{c}{(8)}&\multicolumn{1}{c}{(9)}&\multicolumn{
> 1}{c}{(10)}&\multicolumn{1}{c}{(11)}&\multicolumn{1}{c}{(12)}&\multicolumn{1}{c}{(13)}&\multicolumn{1}{c}{(14)}\\
                    &\multicolumn{1}{c}{est1}&\multicolumn{1}{c}{est2}&\multicolumn{1}{c}{est3}&\multicolumn{1}{c}{est4}&\multicolumn{1}{c}{est5}&\multicolumn{1}{c}{est6}&\multicolumn{1}{c}{est7}&\multicolumn{1}{c}{est8}&\multicolumn{1}{c}{est9}&\mul
> ticolumn{1}{c}{est10}&\multicolumn{1}{c}{est11}&\multicolumn{1}{c}{est12}&\multicolumn{1}{c}{est13}&\multicolumn{1}{c}{est14}\\
\hline
age\_ele1            &      -0.044{$^a$}&                  &      -0.049{$^a$}&                  &      -0.026{$^a$}&                  &                  &                  &                  &                  &                  &                  &
>                   &                  \\
                    &     (0.001)      &                  &     (0.001)      &                  &     (0.001)      &                  &                  &                  &                  &                  &                  &                  & 
>                  &                  \\
[1em]
Age{ijkt}=4$        &                  &      -0.093{$^a$}&                  &      -0.107{$^a$}&                  &      -0.060{$^a$}&                  &      -0.082{$^a$}&                  &      -0.069{$^a$}&                  &      -0.063{$^a$}& 
>                  &      -0.054{$^a$}\\
                    &                  &     (0.003)      &                  &     (0.004)      &                  &     (0.002)      &                  &     (0.004)      &                  &     (0.002)      &                  &     (0.004)      & 
>                  &     (0.003)      \\
[1em]
Age{ijkt}=5$        &                  &      -0.139{$^a$}&                  &      -0.165{$^a$}&                  &      -0.089{$^a$}&                  &      -0.138{$^a$}&                  &      -0.111{$^a$}&                  &      -0.116{$^a$}& 
>                  &      -0.090{$^a$}\\
                    &                  &     (0.004)      &                  &     (0.005)      &                  &     (0.003)      &                  &     (0.004)      &                  &     (0.003)      &                  &     (0.004)      & 
>                  &     (0.003)      \\
[1em]
Age{ijkt}=6$        &                  &      -0.179{$^a$}&                  &      -0.206{$^a$}&                  &      -0.111{$^a$}&                  &      -0.188{$^a$}&                  &      -0.148{$^a$}&                  &      -0.165{$^a$}& 
>                  &      -0.128{$^a$}\\
                    &                  &     (0.005)      &                  &     (0.006)      &                  &     (0.003)      &                  &     (0.005)      &                  &     (0.003)      &                  &     (0.005)      & 
>                  &     (0.003)      \\
[1em]
Age{ijkt}=7$        &                  &      -0.201{$^a$}&                  &      -0.231{$^a$}&                  &      -0.124{$^a$}&                  &      -0.230{$^a$}&                  &      -0.173{$^a$}&                  &      -0.211{$^a$}& 
>                  &      -0.154{$^a$}\\
                    &                  &     (0.005)      &                  &     (0.007)      &                  &     (0.004)      &                  &     (0.006)      &                  &     (0.004)      &                  &     (0.005)      & 
>                  &     (0.004)      \\
[1em]
age\_ele3==     7.0000&                  &      -0.230{$^a$}&                  &      -0.264{$^a$}&                  &      -0.138{$^a$}&                  &      -0.279{$^a$}&                  &      -0.197{$^a$}&                  &      -0.258{$^a$}
> &                  &      -0.182{$^a$}\\
                    &                  &     (0.007)      &                  &     (0.008)      &                  &     (0.005)      &                  &     (0.006)      &                  &     (0.004)      &                  &     (0.006)      & 
>                  &     (0.004)      \\
[1em]
Age{ijkt}=8$        &                  &      -0.252{$^a$}&                  &      -0.298{$^a$}&                  &      -0.153{$^a$}&                  &      -0.311{$^a$}&                  &      -0.223{$^a$}&                  &      -0.297{$^a$}& 
>                  &      -0.209{$^a$}\\
                    &                  &     (0.008)      &                  &     (0.009)      &                  &     (0.005)      &                  &     (0.008)      &                  &     (0.005)      &                  &     (0.008)      & 
>                  &     (0.005)      \\
[1em]
Age{ijkt}=9$        &                  &      -0.258{$^a$}&                  &      -0.290{$^a$}&                  &      -0.160{$^a$}&                  &      -0.346{$^a$}&                  &      -0.251{$^a$}&                  &      -0.336{$^a$}& 
>                  &      -0.242{$^a$}\\
                    &                  &     (0.010)      &                  &     (0.012)      &                  &     (0.007)      &                  &     (0.010)      &                  &     (0.006)      &                  &     (0.010)      & 
>                  &     (0.006)      \\
[1em]
Age{ijkt}=10$       &                  &      -0.287{$^a$}&                  &      -0.332{$^a$}&                  &      -0.170{$^a$}&                  &      -0.433{$^a$}&                  &      -0.293{$^a$}&                  &      -0.423{$^a$}& 
>                  &      -0.283{$^a$}\\
                    &                  &     (0.015)      &                  &     (0.018)      &                  &     (0.011)      &                  &     (0.018)      &                  &     (0.010)      &                  &     (0.017)      & 
>                  &     (0.010)      \\
[1em]
Size$ \_{t-1}$       &                  &                  &      -0.015{$^a$}&      -0.008{$^a$}&      -0.013{$^a$}&      -0.009{$^a$}&                  &                  &                  &                  &                  &                  &
>                   &                  \\
                    &                  &                  &     (0.002)      &     (0.002)      &     (0.001)      &     (0.001)      &                  &                  &                  &                  &                  &                  & 
>                  &                  \\
[1em]
age\_ele2            &                  &                  &                  &                  &                  &                  &      -0.053{$^a$}&                  &      -0.038{$^a$}&                  &                  &                  &
>                   &                  \\
                    &                  &                  &                  &                  &                  &                  &     (0.001)      &                  &     (0.001)      &                  &                  &                  & 
>                  &                  \\
[1em]
Age{ijkt}$          &                  &                  &                  &                  &                  &                  &                  &                  &                  &                  &      -0.050{$^a$}&                  & 
>      -0.035{$^a$}&                  \\
                    &                  &                  &                  &                  &                  &                  &                  &                  &                  &                  &     (0.001)      &                  & 
>     (0.001)      &                  \\
\hline
Observations        &      434593      &      434593      &      434593      &      434593      &      434593      &      434593      &      246772      &      246772      &      246772      &      246772      &      251236      &      251236      & 
>      251236      &      251236      \\
\(R^{2}\)           &       0.574      &       0.575      &       0.603      &       0.605      &       0.676      &       0.677      &       0.507      &       0.507      &       0.593      &       0.595      &       0.495      &       0.495      & 
>       0.578      &       0.578      \\
\hline\hline
\multicolumn{15}{l}{\footnotesize Standard errors in parentheses}\\
\multicolumn{15}{l}{\footnotesize {$^c$} p<0.1, {$^b$} p<0.05, {$^a$} p<0.01}\\
\end{tabular}
}

. eststo clear

. 
. 
. log close
      name:  <unnamed>
       log:  D:\Vicard\VV\re\inprogress\BRV\results\Figure3.log
  log type:  text
 closed on:  29 Sep 2017, 18:21:03
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
